A secure image steganography based on modified matrix encoding using the adaptive region selection technique

This paper introduced an image steganography technique based on modified matrix encoding to enhance the perceptual quality of the stego images. Additionally, more pixel bit-planes are exploited in the data hiding process to improve the embedding capacity. The number of used image layers depends on the size of the given secret message and the texture characteristic of the cover image. The complexity of the pixel block is identified by the difference between the middle pixel and its neighbors. By performing the suitable embedding solutions of modified matrix encoding, the complexity is unchanged by the data hiding stage. Therefore, the used image regions could be determined precisely in the extraction process without using any additional information. The experimental results proved that the stego images created by the proposed approach achieved higher security against statistical and visual steganalysis techniques than the previous methods. The improvement of the security against detection by Ensemble Classifier is four times as secure as the best security performance of the existing methods.

     

An efficient data hiding method based on adaptive directional pixel value differencing (ADPVD)

Steganography is an important secret information communication technology in which one may send messages without others having knowledge of their existence. This paper proposes a new adaptive steganography method for color images using adaptive directional pixel-value differencing (ADPVD). The proposed method increases the capacity of the hidden secret data and improves the security of the stego-color image as well. The hiding capacity of the original PVD method is investigated by considering three directional edges: horizontal, vertical and diagonal directions using color cover image. The cover image is partitioned into 2-pixel blocks in a non-overlapping fashion and scanned in raster-scan order in all three directions. The proposed method adaptively selects the appropriate embedding directions for each color channel according to the largest embedding capacity. The security is improved since different pixel directions are employed adaptively to embed different number of message bits in each color channel. The experimental results show that the proposed method provides both larger embedding capacity and better visual quality of the stego color image compared with other PVD-based algorithms.     

A steganography embedding method based on edge identification and XOR coding

In this paper, we present a novel image steganography algorithm that combines the strengths of edge detection and XOR coding, to conceal a secret message either in the spatial domain or an Integer Wavelet Transform (IWT) based transform domain of the cover image. Edge detection enables the identification of sharp edges in the cover image that when embedding in would cause less degradation to the image quality compared to embedding in a pre-specified set of pixels that do not differentiate between sharp and smooth areas. This is motivated by the fact that the human visual system (HVS) is less sensitive to changes in sharp contrast areas compared to uniform areas of the image. The edge detection method presented here is capable of estimating the exact edge intensities for both the cover and stego images (before and after embedding the message), which is essential when extracting the message. The XOR coding, on the other hand, is a simple, yet effective, process that helps in reducing differences between the cover and stego images. In order to embed three secret message bits, the algorithm requires four bits of the cover image, but due to the coding mechanism, no more than two of the four bits will be changed when producing the stego image. The proposed method utilizes the sharpest regions of the image first and then gradually moves to the less sharp regions. Experimental results demonstrate that the proposed method has achieved better imperceptibility results than other popular steganography methods. Furthermore, when applying a textural feature steganalytic algorithm to differentiate between cover and stego images produced using various embedding rates, the proposed method maintained a good level of security compared to other steganography methods.     

A novel steganalysis for TPVD steganographic method based on differences of pixel difference histogram

Tri-way Pixel Value Differencing (TPVD) steganographic method is a new modified version of another well-known method called PVD, which intents to increase embedding capacity and security of its successor by hiding secret bits in both vertical and diagonal edges of a cover image, in addition to the horizontal edges used in PVD. In this paper, it is shown that the histogram of difference values of a stego image under the TPVD algorithms is vulnerable to a particular statistical analysis. So, a new steganalytic measure named Growing Anomalies is introduced that its value has a linear relationship with secret message rate. It is shown empirically and theoretically that proposed steganalysis method based on this measure can estimate the amount of secret bits with a negligible error rate. The proposed steganalyser can classify test images as stego or cover with 97% accuracy when they contain more that 10% secret data. Implementation results indicate that proposed method can estimate secret message rate with an average accuracy of 95%.     

利用像素置换的自适应可逆信息隐藏

目的 像素置换作为一种可逆信息隐藏方式具有良好的抗灰度直方图隐写分析能力,但嵌入容量偏小一直是其缺陷。针对这一问题,提出了一种基于像素置换的自适应可逆信息隐藏算法。方法 首先,与传统2×2像素块结构相比构造了尺寸更小的像素对结构,使得载体图像可以被更稠密地分割,为嵌入容量的提升提供了基数条件。其次,提出适用于该新像素结构的可嵌像素对（EPP）筛选条件,避免嵌入过程引起图像质量大幅下降。之后,根据EPP的灰度趋势差异对其进行自适应预编码,提高Huffman编码压缩比,进一步提升算法嵌入容量。最终,通过像素置换嵌入信息。结果 与2×2像素块结构的非自适应图像隐写算法相比,在同样保证灰度直方图稳定性的情况下该算法的PSNR提高了32%左右,嵌入容量提高了95%以上。其中自适应性对嵌入容量提升的贡献极大。结论 本文算法同时具有抗灰度直方图隐写分析能力与高嵌入容量性的可逆信息隐藏。算法构造了更高效的可嵌单位,并且针对不同载体图像的特点对其可嵌区域进行差异化编码。实验结果表明,本文算法在具有更好的不可见性的同时,嵌入容量得到大幅提升。     

LSB based non blind predictive edge adaptive image steganography

Image steganography is the art of hiding secret message in grayscale or color images. Easy detection of secret message for any state-of-art image steganography can break the stego system. To prevent the breakdown of the stego system data is embedded in the selected area of an image which reduces the probability of detection. Most of the existing adaptive image steganography techniques achieve low embedding capacity. In this paper a high capacity Predictive Edge Adaptive image steganography technique is proposed where selective area of cover image is predicted using Modified Median Edge Detector (MMED) predictor to embed the binary payload (data). The cover image used to embed the payload is a grayscale image. Experimental results show that the proposed scheme achieves better embedding capacity with minimum level of distortion and higher level of security. The proposed scheme is compared with the existing image steganography schemes. Results show that the proposed scheme achieves better embedding rate with lower level of distortion.     

面向可逆图像处理网络的可证安全自然隐写

目的 自然隐写是一种基于载体源转换的图像隐写方法,基本思想是使隐写后的图像具有另一种载体的特征,从而增强隐写安全性。但现有的自然隐写方法局限于对图像ISO(International Standardization Organization)感光度进行载体源转换,不仅复杂度高,而且无法达到可证安全性。为了提高安全性,本文结合基于标准化流的可逆图像处理模型,在隐空间完成载体源转换,同时通过消息映射的设计做到了可证安全的自然隐写。方法 利用目前发展迅速的基于可逆网络的图像处理方法将图像可逆地映射到隐空间,通过替换使用的隐变量完成载体源的转换,从而避免对原始图像复杂的建模。同时,改进了基于拒绝采样的消息映射方法,简单地从均匀分布中采样以获得需要的条件分布,高效地将消息嵌入到隐变量中,并且保证了嵌入消息后的分布与原本使用的分布一致,从而实现了可证安全的自然隐写。结果 针对图像质量、隐写容量、消息提取准确率、隐写安全性和运行时间进行了实验验证,结果表明在使用可逆缩放网络和可逆去噪网络时能够在每个像素值上平均嵌入5.625 bit消息,且具有接近99%的提取准确率,同时隐写分析网络SRNet(st...     

A steganalysis by adjacency pixel bits structure

Embedding of confidential data in the least significant bit of an image is still an attractive method of steganography. Utilizing the full capacity of cover images by embedding one bit of data per pixel, using methods such as LSB flipping or LSB matching, usually decreases the security, making the algorithm vulnerable to steganalytic attacks. And then, it is proposed by an efficient high payload ±1 data embedding scheme(EPES) based on a special two variable binary function. This function uses the information of the least two significant bit planes of the cover image for the embedding and extraction purposes. Rather than randomly selecting +1 or −1, EPES achieves higher embedding efficiencies by choosing the correct modification component. The steganalytic method based on sample pair analysis (SPA) cannot effectively detect EPES. Hence, we propose a steganalysis by constructing adjacency pixel bits structure (SAP). The resulting detection algorithm is simple and fast. Analytical and experimental results demonstrate that the proposed method provides higher detecting efficiency than the other steganalysis.     

An LSB based novel data hiding method using extended LBP

In this paper we have proposed an LSB based data hiding method. Here, first cover image is encoded by LBP based method (call as ELBP). In ELBP method, a 3 × 3 block is encoded by k bits (1 ≤ k ≤ 9) respect to the central pixel. For data hiding purpose, the cover image is encoded by ELBP then r (1 ≤ r < k) bits are embedded into each neighbor pixel by replacing least r bits of the encoded stream and then modified pixel is processed by OPAP method to improve the quality of the stego image. Proposed method gives high quality stego images with higher embedding rate compare to the state-of-the-art methods. The security of the proposed data hiding method is tested against the attacks like RS steganalysis and Chi-square attack and these methods fail to detect hidden data.

     

Steganalysis of stochastic modulation steganography

Steganography[1] conceals the occurrence and real purpose of communication by em- bedding message into the cover medium, such as an image, audio or video. Because im- age is widely used in Internet and has much redundancy, it has been one of the most im- …     

Performance enhanced image steganography systems using transforms and optimization techniques

Image steganography is the art of hiding highly sensitive information onto the cover image. An ideal approach to image steganography must satisfy two factors: high quality of stego image and high embedding capacity. Conventionally, transform based techniques are widely preferred for these applications. The commonly used transforms for steganography applications are Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) etc. In this work, frequency domain transforms such as Fresnelet Transform (FT) and Contourlet Transform (CT) are used for the data hiding process. The secret data is normally hidden in the coefficients of these transforms. However, data hiding in transform coefficients yield less accurate results since the coefficients used for data hiding are selected randomly. Hence, in this work, optimization techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used for improving the performance of the steganography system. GA and PSO are used to find the best coefficients in order to hide the Quick Response (QR) coded secret data. This approach yields an average PSNR of 52.56 dB and an embedding capacity of 902,136 bits. These experimental results validate the practical feasibility of the proposed methodology for security applications.     

Current status and key issues in image steganography: A survey

Steganography and steganalysis are the prominent research fields in information hiding paradigm. Steganography is the science of invisible communication while steganalysis is the detection of steganography. Steganography means “covered writing” that hides the existence of the message itself. Digital steganography provides potential for private and secure communication that has become the necessity of most of the applications in today’s world. Various multimedia carriers such as audio, text, video, image can act as cover media to carry secret information. In this paper, we have focused only on image steganography. This article provides a review of fundamental concepts, evaluation measures and security aspects of steganography system, various spatial and transform domain embedding schemes. In addition, image quality metrics that can be used for evaluation of stego images and cover selection measures that provide additional security to embedding scheme are also highlighted. Current research trends and directions to improve on existing methods are suggested.     

An adaptive color image steganography method using adjacent pixel value differencing and LSB substitution technique

Abstract

Steganography is a data-concealing technique that provides a covert communication. This paper proposes a spatial domain color steganography method that uses a neighboring pixel-pair differencing concept to enhance the embedding capacity. The proposed method considers the distortion tolerance capacity of each color plane and the difference value between two neighboring pixels while deciding the number of bits that can be concealed in that pixel-pair. Each plane is divided into some disjoint blocks of size 3?×?3 pixels. The method forms eight pairs of pixels in one block using the eight-neighboring pixel concept, which enables the method to utilize all the edge pixels in all probable directions. It also uses the XOR encoding technique before the embedding process. This step provides an additional layer of security to the secret information. The simulation results show that the proposed method is able to achieve a high embedding capacity with good visual quality as per the calculation of imperceptibility metrics. The robustness of the method is tested by RS steganalysis and pixel difference histogram analysis. Further, a comparison between the proposed method and the existing methods on the basis of embedding capacity and stego image quality is shown.     

发送方可否认图像隐写

目的 图像隐写是指将秘密信息隐藏到载体图像中,生成含密图像并在公共信道中传输。隐写分析旨在识别图像中是否隐藏秘密信息。不论何种隐写方案,都会在一定程度上被隐写分析识破,从而导致胁迫攻击,即攻击者找到发送方或接收方,胁迫其提交经过验证的秘密信息。为了保护秘密信息的隐蔽通信,对抗胁迫攻击的可否认方案亟待研究。在密码学领域,为了对抗胁迫攻击,已经提出了可否认加密的概念及相关方案并受到关注与研究。而在隐写领域,有研究提出可否认隐写的概念并设计了接收方可否认隐写的框架,但没有发送方可否认隐写的相关研究。对此,本文讨论发送方可否认隐写。方法 设计方案的通用框架,并构造两个方案:基于可逆网络的发送方可否认图像隐藏方案和基于可否认加密的发送方可否认图像隐写方案。在发送方可否认隐写的框架下,发送方可使用虚假的秘密信息生成与攻击者手中相同的含密图像,以欺骗攻击者,逃脱胁迫攻击,保护真实的秘密信息。结果 实验结果表明,两个方案都是可行且有效的,与原始隐写方案相比,可否认方案达到了发送方可否认功能的同时,均不会显著降低含密图像的视觉质量(峰值信噪比(peak signal-to-noise ratio,PSN...     

A novel joint secret image sharing and robust steganography method using wavelet

In this paper a data hiding method is proposed based on the combination of a secret sharing technique and a novel steganography method using integer wavelet transform. In this method in encoding phase, first a secret image is shared into n shares, using a secret sharing technique. Then, the shares and Fletcher-16 checksum of shares are hidden into n cover images using proposed wavelet based steganography method. In decoding phase, t out of n stego images are required to recover the secret image. In this phase, first t shares and their checksums are extracted from t stego images. Then, by using the Lagrange interpolation the secret image is revealed from the t shares. The proposed method is stable against serious attacks, including RS and supervisory training steganalysis methods, it has the lowest detection rate under global feature extraction classifier examination compared to the state-of-the-art techniques. Experimental results on a set of benchmarks showed that this method outperforms conventional methods in offering a high secure and robust mechanism for joining secret image sharing and steganography.     

基于条件可逆网络的生成式图像隐写算法

近年来,随着生成模型的广泛使用,生成式隐写领域得到了快速发展。生成式隐写是在图像合成过程中隐藏信息的技术。它无需真实图像参与,只需秘密消息驱动生成模型即可合成载密图像。然而,现有方法无法控制生成的图像内容,因此不能保证隐蔽通信行为的安全性。针对上述问题,本文提出了基于条件可逆网络(Conditional Invertible Neural Network,cINN)的生成式图像隐写术steg-Cinn。在本文中,我们将信息隐藏建模为图像着色问题,并将秘密信息嵌入到灰度图像的颜色信息中。首先,我们使用映射模块将二进制秘密信息转换为服从标准正态分布的隐变量。而后,我们以灰度图像作为先验来指导着色过程,使用条件可逆网络来将隐变量映射为颜色信息。其中steg-Cinn生成的彩色图像匹配灰度图像的语义内容,从而保证了隐蔽通信的行为安全。对比实验结果表明,本文方法能够控制生成的图像内容并且使得合成颜色真实自然,在视觉隐蔽性方面表现良好。在统计安全性方面,本文方法的隐写分析检测正确率为56.28%,说明它能够抵御隐写分析检测。此外,本文方法在比特消息提取方面可以实现100%正确提取,这种情况下的隐藏容量是2.00 bpp。因此,与现有方法相比,本文方法在图像质量、统计安全性、比特提取正确率和隐藏容量方面取得了良好的综合性能表现。迄今为止,本文方法是在图像隐写术中首次使用cINN的工作。考虑到任何信息都可以转换为二进制形式,我们可以在图像中隐藏任意类型的数据,因此本文方法在现实世界里也具备实用价值。     

Reversible data hiding for high quality images exploiting interpolation and direction order mechanism

Reversible data hiding can restore the original image from the stego image without any distortion after the embedded secret message is exactly extracted. In this paper, a novel, reversible, data hiding scheme for high quality images is proposed in spatial domain. To increase embedding capacity and enhance image quality, the proposed scheme classifies all pixels as wall pixels and non-wall pixels. For wall pixel, the interpolation error is used to embed secret data over the interpolation prediction method. In contrast, the difference value between the non-wall pixel and its parent pixel, which is defined by the direction order, is computed to hide secret data based on the histogram shifting. The experimental results demonstrate that our scheme provides a larger payload and a better image quality than some existing schemes. Moreover, the performance of the proposed scheme is more stable for different images.     

生成对抗网络驱动的图像隐写与水印模型

目的 图像信息隐藏包括图像隐写术和图像水印技术两个分支。隐写术是一种将秘密信息隐藏在载体中的技术,目的是为了实现隐秘通信,其主要评价指标是抵御隐写分析的能力。水印技术与隐写术原理类似,但其是通过把水印信息嵌入到载体中以达到保护知识产权的作用,追求的是防止水印被破坏而尽可能地提高水印信息的鲁棒性。研究者们试图利用生成对抗网络（generative adversarial networks,GANs）进行自动化的隐写算法以及鲁棒水印算法的设计,但所设计的算法在信息提取准确率、嵌入容量和隐写安全性或水印鲁棒性、水印图像质量等方面存在不足。方法 本文提出了基于生成对抗网络的新型端到端隐写模型（image information hiding-GAN,IIH-GAN）和鲁棒盲水印模型（image robust blind watermark-GAN,IRBW-GAN）,分别用于图像隐写术和图像鲁棒盲水印。网络模型中使用了更有效的编码器和解码器结构SE-ResNet（squeeze and excitation ResNet）,该模块根据通道之间的相互依赖性来自适应地重新校准通道方式的特征响应。结果 实验结果表明隐写模型IIH-GAN相对其他方法在性能方面具有较大改善,当已知训练好的隐写分析模型的内部参数时,将对抗样本加入到IIH-GAN的训练过程,最终可以使隐写分析模型的检测准确率从97.43%降低至49.29%。该隐写模型还可以在256×256像素的图像上做到高达1 bit/像素（bits-per-pixel）的相对嵌入容量;IRBW-GAN水印模型在提升水印嵌入容量的同时显著提升了水印图像质量以及水印提取正确率,在JEPG压缩的攻击下较对比方法提取准确率提高了约20%。结论 本文所提IIH-GAN和IRBW-GAN模型在图像隐写和图像水印领域分别实现了领先于对比模型的性能。     

引入超分辨率下采样误差的图像边信息估计隐写

目的由于空域图像下采样过程中提供的量化误差边信息能够有效提升隐写安全性,为了得到下采样之前的高分辨率图像,提出一种基于超分辨率网络的空域图像边信息估计隐写方法。方法受原始下采样边信息隐写方法的启发,使用超分辨率网络生成被称为预载体的高分辨率图像。同时利用现有的空域图像对称失真算法得到每个像素点的修改失真,然后以浮点型精度对预载体下采样,得到和载体同分辨率的图像形式,利用对应像素点间的差值指导像素点的修改方向,实现基于初始失真的非对称失真调整。首先以峰值信噪比和极性估计准确率为指标对比了多种超分辨率网络以及基于传统插值方法的上采样性能,并通过调整初始失真分别进行隐写和隐写分析实验,选择使安全性提升最大的残差通道注意力机制网络及其对应调整系数作为本文的下采样边信息估计隐写方法。结果使用隐写领域中常用的3个数据库、两种传统初始失真函数以及两类隐写分析方法进行实验。在跨数据集的隐写安全性上,相比传统隐写方法,在对抗基于手工特征和基于深度学习的隐写分析时,本文方法的安全性均有显著提升,如在测试集载体图像上,嵌入率为0.5 bit/像素时,安全性分别提升6.67%和6.9%;在训练集载体图像上,本...     

结合块旋转和马赛克拼图的生成式伪装方法

目的 搜索式无载体信息隐藏容量低,涉及大量载体密集传输;纹理合成无载体隐藏只能生成简单质地的纹理图像;马赛克拼图信息隐藏尽管能产生有意义图像,但需修改嵌入参数。针对以上问题,提出一种结合块旋转和马赛克拼图的生成式伪装方法。方法 将灰度图像进行圆形化并添加随机转角构建马赛克,通过随机坐标决定秘密信息的隐藏位置;在隐藏位置,根据密钥和放置位置来放置代表秘密比特串的圆形图像和施加认证转角,对于非隐藏位置则放置最接近圆形图像来掩盖秘密信息;将放置过程产生的偏差通过误差扩散分散给周围未处理像素。在提取时,结合质心旋转匹配提取秘密比特并进行转角认证。结果 采用圆形图像表达秘密信息而不涉及修改式嵌入,通过马赛克拼图产生有意义含密掩体,可通过质心旋转匹配提取秘密比特并进行转角认证。对密钥严格依赖,在遭受质量因子为50~80的JPEG压缩和随机转角攻击时,秘密信息可完整恢复,在遭受强度为8%~20%的椒盐噪声攻击时,提取信息的误码率低于5%,且对秘密信息的认证成功率均在80%以上。结论 所提方法具有较好的抗攻击能力,可抵御信道攻击且具备较高的安全性。